{"id":1172,"date":"2016-11-05T06:42:45","date_gmt":"2016-11-05T01:12:45","guid":{"rendered":"http:\/\/data-flair.training\/blogs\/?p=1172"},"modified":"2021-08-25T22:33:49","modified_gmt":"2021-08-25T17:03:49","slug":"features-of-hadoop-and-design-principles","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/features-of-hadoop-and-design-principles\/","title":{"rendered":"10 Features Of Hadoop That Made It The Most Popular"},"content":{"rendered":"<p><strong>Have you ever thought why companies adopt Hadoop as a solution to Big Data Problems?<\/strong><\/p>\n<p>In this article, we are going to study the essential features of Hadoop that make Hadoop so popular. The article enlists various Hadoop features like open source, scalability, fault tolerance, high availability, etc. that make Hadoop the <strong>most popular big data tool<\/strong>.<\/p>\n<p>Let us first begin with a short introduction to Hadoop.<\/p>\n<h3>What is Hadoop?<\/h3>\n<p>Hadoop is a software framework developed by the Apache Software Foundation for distributed storage and processing of huge amounts of datasets. <a href=\"https:\/\/data-flair.training\/blogs\/hadoop-tutorial\/\"><strong>Hadoop<\/strong><\/a> consists of 3 core components :<\/p>\n<h4>1. HDFS (High Distributed File System)<\/h4>\n<p>It is the<strong> storage layer of Hadoop<\/strong>. Files in HDFS are broken into block-sized chunks. HDFS consists of two types of nodes that is, NameNode and DataNodes.<\/p>\n<ul>\n<li>NameNode stores metadata about blocks location.<\/li>\n<li>DataNodes stores the block and sends block reports to NameNode in a definite time interval.<\/li>\n<\/ul>\n<h4>2. MapReduce<\/h4>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/hadoop-mapreduce-tutorial\/\">MapReduce<\/a><\/strong> is the <strong>processing layer in Hadoop<\/strong>. It is a software framework for writing an application that performs distributed processing.<\/p>\n<h4>3. YARN<\/h4>\n<p>It is the <strong>resource management layer<\/strong>. <strong>YARN<\/strong> is responsible for resource allocation and job scheduling.<\/p>\n<p>To study in detail Hadoop and its component, go through the <a href=\"https:\/\/data-flair.training\/blogs\/hadoop-architecture\/\"><strong>Hadoop architecture<\/strong><\/a> article.<\/p>\n<p>Let us now begin with the Features of Hadoop.<\/p>\n<h2>Features of Hadoop<\/h2>\n<p>Apache Hadoop is the most popular and powerful big data tool, Hadoop provides the world&#8217;s most reliable storage layer. In this section of the features of Hadoop, let us discuss various key features of Hadoop.<\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-76438\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop.jpg\" alt=\"features of hadoop\" width=\"802\" height=\"420\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop.jpg 802w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/11\/features-of-hadoop-520x272.jpg 520w\" sizes=\"auto, (max-width: 802px) 100vw, 802px\" \/><\/a><\/p>\n<h3>1. Hadoop is Open Source<\/h3>\n<p>Hadoop is an open-source project, which means its source code is available free of cost for inspection, modification, and analyses that allows enterprises to modify the code as per their requirements.<\/p>\n<h3>2. Hadoop cluster is Highly Scalable<\/h3>\n<p>Hadoop cluster is scalable means we can add any number of nodes (<strong>horizontal scalable<\/strong>) or increase the hardware capacity of nodes (<strong>vertical scalable<\/strong>) to achieve high computation power. This provides horizontal as well as vertical scalability to the Hadoop framework.<\/p>\n<h3>3. Hadoop provides Fault Tolerance<\/h3>\n<p>Fault tolerance is the most important feature of Hadoop. <a href=\"https:\/\/hadoop.apache.org\/docs\/r1.2.1\/hdfs_design.html\">HDFS<\/a> in Hadoop 2 uses a <strong>replication mechanism<\/strong> to provide fault tolerance.<\/p>\n<p>It creates a replica of each block on the different machines depending on the replication factor (by default, it is 3). So if any machine in a cluster goes down, data can be accessed from the other machines containing a replica of the same data.<\/p>\n<p>Hadoop 3 has replaced this replication mechanism by <strong>erasure coding<\/strong>. Erasure coding provides the same level of fault tolerance with less space. With Erasure coding, the storage overhead is not more than 50%.<\/p>\n<p>Read <a href=\"https:\/\/data-flair.training\/blogs\/hadoop-hdfs-erasure-coding\/\"><strong>Erasure coding<\/strong><\/a> article to learn the erasure coding algorithm.<\/p>\n<h3>4. Hadoop provides High Availability<\/h3>\n<p>This feature of Hadoop ensures the high availability of the data, even in unfavorable conditions.<\/p>\n<p>Due to the fault tolerance feature of Hadoop, if any of the DataNodes goes down, the data is available to the user from different DataNodes containing a copy of the same data.<\/p>\n<p>Also, the high availability Hadoop cluster consists of 2 or more running NameNodes (active and passive) in a hot standby configuration. The active node is the NameNode, which is active. Passive node is the standby node that reads edit logs modification of active NameNode and applies them to its own namespace.<\/p>\n<p>If an active node fails, the passive node takes over the responsibility of the active node. Thus even if the NameNode goes down, files are available and accessible to users.<\/p>\n<h3>5. Hadoop is very Cost-Effective<\/h3>\n<p>Since the Hadoop cluster consists of nodes of commodity hardware that are inexpensive, thus provides a cost-effective solution for storing and processing big data. Being an open-source product, Hadoop doesn\u2019t need any license.<\/p>\n<h3>6. Hadoop is Faster in Data Processing<\/h3>\n<p>Hadoop stores data in a distributed fashion, which allows data to be processed distributedly on a cluster of nodes. Thus it provides lightning-fast processing capability to the Hadoop framework.<\/p>\n<h3>7. Hadoop is based on Data Locality concept<\/h3>\n<p>Hadoop is popularly known for its data locality feature means moving computation logic to the data, rather than moving data to the computation logic. This features of Hadoop reduces the bandwidth utilization in a system.<\/p>\n<p>To install and configure Hadoop follow this <a href=\"https:\/\/data-flair.training\/blogs\/installation-of-hadoop-3-on-ubuntu\/\"><strong>installation guide<\/strong><\/a>.<\/p>\n<h3>8. Hadoop provides Feasibility<\/h3>\n<p>Unlike the traditional system, Hadoop can process unstructured data. Thus provide feasibility to the users to analyze data of any formats and size.<\/p>\n<h3>9. Hadoop is Easy to use<\/h3>\n<p>Hadoop is easy to use as the clients don\u2019t have to worry about distributing computing. The processing is handled by the framework itself.<\/p>\n<h3>10. Hadoop ensures Data Reliability<\/h3>\n<p>In Hadoop due to the replication of data in the cluster, data is stored reliably on the cluster machines despite machine failures.<\/p>\n<p>The framework itself provides a mechanism to ensure data reliability by Block Scanner, Volume Scanner, Disk Checker, and Directory Scanner. If your machine goes down or data gets corrupted, then also your data is stored reliably in the cluster and is accessible from the other machine containing a copy of data.<\/p>\n<p><strong>Also, explore\u00a0<a href=\"https:\/\/data-flair.training\/blogs\/what-is-new-in-hadoop-3\/\">10 changes in Hadoop 3<\/a>\u00a0that makes it unique and fast.<\/strong><\/p>\n<h2>Summary<\/h2>\n<p>In short, we can say that Hadoop is an open-source framework. Hadoop is best known for its fault tolerance and high availability feature. Hadoop clusters are scalable. The Hadoop framework is easy to use.<\/p>\n<p>It ensures fast data processing due to distributed processing. Hadoop is cost-effective. 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In this article, we are going to study the essential features of Hadoop that make Hadoop so popular. The&#46;&#46;&#46;<\/p>\n","protected":false},"author":7,"featured_media":76438,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[22],"tags":[3326,4550,18900,21879,21858,16842,5262,5342,22003],"class_list":["post-1172","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hadoop","tag-data-locality-in-hadoop","tag-fault-tolerance-in-hadoop","tag-features-of-hadoop","tag-features-of-hadoop-distributed-file-system","tag-features-of-hdfs","tag-hadoop-3-features","tag-hadoop-high-availability","tag-hadoop-tutorial","tag-mapreduce-features"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>10 Features Of Hadoop That Made It The Most Popular - DataFlair<\/title>\n<meta name=\"description\" content=\"Features of Hadoop- Characteristics of Hadoop, scalability, reliability, fault tolerance, high availability, data locality, speculative execution, distributed process\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/features-of-hadoop-and-design-principles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"10 Features Of Hadoop That Made It The Most Popular - 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